{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 《python数据可视化之matplotlib实践》\n",
    "## matplotlib可视化学习-chapter-6\n",
    "## 进阶 图形样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "mpl.rcParams['font.sans-serif'] = ['FangSong']  # 显示中文\n",
    "mpl.rcParams['axes.unicode_minus'] = False # 不使用unicode_minus模式处理坐标轴轴线为负数的情况，\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "radii = np.linspace(0,1,100)\n",
    "theta = 2*np.pi*radii\n",
    "\n",
    "plt.plot(theta, radii)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "radii = np.linspace(0,1,100)\n",
    "theta = 2*np.pi*radii\n",
    "ax = plt.subplot(111,polar=True)  # 指定极坐标形式\n",
    "\n",
    "ax.plot(theta, radii)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 非等分画布\n",
    "\n",
    "x = np.linspace(0, 2*np.pi, 100)\n",
    "y = np.cos(x) * np.sin(x)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(1,2,1)  # 画布分成1行2列，取第一列\n",
    "ax1.margins(0.03)  # 设置数据的空白区域\n",
    "ax1.plot(x,y,color='r')\n",
    "\n",
    "ax2 = fig.add_subplot(2,2,2) # 画布分成2行2列，取第2个\n",
    "ax2.margins(0.7,0.7)# 设置数据的空白区域\n",
    "ax2.plot(x,y,color='g')\n",
    "\n",
    "\n",
    "ax3 = fig.add_subplot(2,2,4) # 画布分成2行2列，取第4个\n",
    "ax3.margins(0.1,0.1)\n",
    "ax3.plot(x,y,color='b')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 也可以直接使用plt\n",
    "plt.subplot(121)\n",
    "plt.margins(0.03)\n",
    "plt.plot(x,y,color='r')\n",
    "plt.subplot(222)\n",
    "plt.margins(0.3,0.7)\n",
    "plt.plot(x,y,color='g')\n",
    "plt.subplot(224)\n",
    "plt.plot(x,y,color='b')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## subplot只能等分画布，不能设置不同大小\n",
    "## subplot2grid的`rowspan`,`colspan`可以实现非等分画布\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subplot2grid(shape, loc, colspan, rowspan)\n",
    "# 实现非等分画布\n",
    "\n",
    "plt.subplot2grid((4,4),(0,0), colspan=3) # 整个画布分均为4行4列，从（0，0）开始，占3列\n",
    "x = np.linspace(0,4,10)\n",
    "y = np.random.randn(10)\n",
    "plt.scatter(x,y,c='b')\n",
    "plt.title('scatter')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (0,3)) # 整个画布分均为4行4列，从（0,3）开始，默认占1行1列\n",
    "plt.title('empty fig')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4),(1,0), rowspan=3,colspan=2) # 整个画布分均为4行4列，从（1,0）开始，占3行2列\n",
    "plt.plot(range(10), range(10),color='g')\n",
    "plt.grid(color='gray',alpha=0.4, linestyle=':')\n",
    "plt.title('line')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (1,2),colspan=2) # 整个画布分均为4行4列，从（0,3）开始，默认占1行1列\n",
    "plt.title('empty fig')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (2,2), colspan=2)\n",
    "plt.plot(x, np.sin(x), marker='*',c='r')\n",
    "plt.title('sin(x)-1')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (3,2))\n",
    "plt.plot(x, np.sin(x), marker='*',c='m')\n",
    "plt.title('sin(x)-2')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (3,3))\n",
    "plt.plot(x, np.cos(x), marker='*',c='k')\n",
    "plt.title('cos(x)')\n",
    "\n",
    "\n",
    "# 整个画布的title\n",
    "plt.suptitle(\"整个画布的title\",fontsize=20,color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 解决子图标题、坐标轴遮挡问题\n",
    "\n",
    "fig.tight_layout()#调整整体空白\n",
    "  \n",
    "  plt.subplots_adjust(wspace =0, hspace =0)#调整子图间距\n",
    "  \n",
    "  plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)\n",
    "  \n",
    "  pad：分数（相对于 font-size），控制各个子图边界或 figure 边界的内边距。\n",
    "\n",
    "h_pad and w_pad：单位为英寸，控制相邻子图的高或者宽的边距。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# subplot2grid(shape, loc, colspan, rowspan)\n",
    "# 实现非等分画布\n",
    "plt.tight_layout(pad=1, w_pad=0.5, h_pad=1.0)\n",
    "\n",
    "plt.subplot2grid((4,4),(0,0), colspan=3) # 整个画布分均为4行4列，从（0，0）开始，占3列\n",
    "# plt.subplots_adjust(wspace =0.2, hspace =1)#调整子图间距\n",
    "\n",
    "x = np.linspace(0,4,10)\n",
    "y = np.random.randn(10)\n",
    "plt.scatter(x,y,c='b')\n",
    "plt.title('scatter')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (0,3)) # 整个画布分均为4行4列，从（0,3）开始，默认占1行1列\n",
    "plt.title('empty fig')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4),(1,0), rowspan=3,colspan=2) # 整个画布分均为4行4列，从（1,0）开始，占3行2列\n",
    "plt.plot(range(10), range(10),color='g')\n",
    "plt.grid(color='gray',alpha=0.4, linestyle=':')\n",
    "plt.title('line')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (1,2),colspan=2) # 整个画布分均为4行4列，从（0,3）开始，默认占1行1列\n",
    "plt.title('empty fig')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (2,2), colspan=2)\n",
    "plt.plot(x, np.sin(x), marker='*',c='r')\n",
    "plt.title('sin(x)-1')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (3,2))\n",
    "plt.plot(x, np.sin(x), marker='*',c='m')\n",
    "plt.title('sin(x)-2')\n",
    "\n",
    "\n",
    "plt.subplot2grid((4,4), (3,3))\n",
    "plt.plot(x, np.cos(x), marker='*',c='k')\n",
    "plt.title('cos(x)')\n",
    "\n",
    "\n",
    "# 整个画布的title\n",
    "plt.suptitle(\"整个画布的title\",fontsize=20,color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## subplot 与 subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cb71b7550>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD8CAYAAAB5Pm/hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADHxJREFUeJzt3E+InXe5wPHv08SUsbHImFETylC9AbMoKOkYcO4mXVgnoFR00YVWCuLAxYUhSBX/EYK9XLh1kQtu5oL0cnO1koWVbqZujEIW1gyt4aJZxMClNUGnmahUU+vicTGvnrmnJ3Pec+adM+nT72f1yzm/mXn6a8+3J++ccyIzkSTVdcdODyBJ2l6GXpKKM/SSVJyhl6TiDL0kFWfoJam4VqGPiIeH3H8yIr4QEZ/uZixJUleGhj4iPgY8usn9h4GbmXkaOBoRe7obT5K0VUNDn5nPAL/dZMsx4Hyzvgwc6WAuSVJHdnfwPQ4Aq816Ddg/aFNELAKLAHfdddf9hw4d6uBHS9Kbx8rKysuZOTPq13UR+o0CGPiZCpm5BCwBzM3N5YULFzr+0ZJUW0T83zhf18Wrbq4C+5r1NHCtg+8pSerISKGPiF0R8c6+m5eB+WZ9EHiui8EkSd1o86qbh4AHIuJBYA54YuP9mbkCTEXEceBcZv51WyaVJI1l6DX6zPwh8MMNN/1swJ5TXQ4lSeqO74yVpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpuN1tNkXESeAGcD0zzwy4fxb4MLAGTGXmd7scUpI0vqHP6CPiMHAzM08DRyNiz4BtjwDfycwfAO+KiLs7nlOSNKY2l26OAeeb9WXgyIA9u4APNeu3Aq9tfTRJUhfaXLo5AKw26zVg/4A9TwDPRsSvgKcz89X+DRGxCCwCzM7OjjetJGlko/4yNoAccPs88DjwC5qY98vMpcycy8y5mZmZEX+sJGlcbUJ/FdjXrKeBawP2fCQzlzPz28CvI+K+rgaUJG1Nm9Avs/6MHeAgcDEipvv2/H7D+iXgdZduJEk7Y2joM3MFmIqI48A5YAE40bftexHxSER8AnglMy93PqkkaSytXkefmaf6bjrbd/8V4EpXQ0mSuuM7YyWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9Jxe1usykiTgI3gOuZeeYWez4LvALcn5mPdTahJGlLhj6jj4jDwM3MPA0cjYg9A/bMA9cy8/vAL7sfU5I0rjaXbo4B55v1ZeDIgD2fBH4OkJlPdjKZJKkTbS7dHABWm/UasH/AnnuBj0bENPD2zPx6/4aIWAQWAWZnZ8caVpI0ulF/GRtADrj9bcBzmfktICPidSXPzKXMnMvMuZmZmTFGlSSNo03orwL7mvU0cG3AnpeBF5v1iwx+1i9J2gFtQr8MzDfrg8DF5hLNRj8F5pr1PuBKN+NJkrZqaOgzcwWYiojjwDlgATjRt+2/gAci4hPAlcxcRZJ0W2j1OvrMPNV309m++28Cr/sFrCRp5/nOWEkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekorb3WZTRJwEbgDXM/PMJvsWgHdn5pOdTCdJ2rKhz+gj4jBwMzNPA0cjYs8t9gXw8Y7nkyRtUZtLN8eA8836MnDkFvseBH7UxVCSpO60Cf0BYLVZrwH7+zdExC5gb3P/QBGxGBEXIuLC6urqrbZJkjo26i9jA8gBtx8Dljf7wsxcysy5zJybmZkZ8cdKksbVJvRXgX3Nehq4NmDPXuCDwAeAQxFxTzfjSZK2qk3ol4H5Zn0QuBgR0xs3ZOZTmXkOeAG4lJkvdTqlJGlsQ0OfmSvAVEQcB84BC8CJ/n1N/BeAByLCazOSdJto9Tr6zDzVd9PZAXvWgC93MZQkqTu+M1aSijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVNzuNpsi4iRwA7iemWcG3L8XeBj4I3AgM093OaQkaXxDn9FHxGHgZhPvoxGxZ8C2R4DnM/MscG9E3N3xnJKkMbW5dHMMON+sLwNHBuy5BNzZrBN4beujSZK60ObSzQFgtVmvAfv7N2TmjwEi4s7mz6/274mIRWARYHZ2dsxxJUmjGvWXscH6M/ZbeRT45qA7MnMpM+cyc25mZmbEHytJGleb0F8F9jXraeDaoE0RsQD8JDPXOppNktSBNqFfBuab9UHgYkRMb9wQEfcAd2TmpYh4T0Qc7HhOSdKYhoY+M1eAqYg4DpwDFoATfdv+BfhMRDwFPMP63wIkSbeBVq+jz8xTfTed7bv/q51NJEnqlO+MlaTiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqbjdbTZFxEngBnA9M88MuH8X8G/A74CLmflsl0NKksY39Bl9RBwGbmbmaeBoROwZsO0h4EJm/jvwqY5nlCRtQZtLN8eA8836MnBkyJ4/R8Q9HcwmSepAm0s3B4DVZr0G7G+556WNGyJiEVhs/viXiPjfkaetaR/w8k4PcZvwLHo8ix7Poud943xRq2v0GwSQ4+zJzCVgCSAiLmTm3Ig/uyTPosez6PEsejyLnoi4MM7Xtbl0c5X1/6MCTAPXxtwjSdoBbUK/DMw364PAxYiY3mTPVGb+pqP5JElbNDT0mbkCTEXEceAcsACc6Nv2NDAXEV8C/qfFz10acc7KPIsez6LHs+jxLHrGOovIHHbJXZL0RuY7YyWpOEMvScWN+vLKkfjRCT0tzmIv8DDwR+BA807kkoadxYZ9C8C7M/PJCY02cW3OIiI+C7wC3J+Zj01wvIlq8RiZBT7M+nt1pjLzu5OdcHIi4uHM/P4m95+kxWPo77btGb0fndDT8iweAZ7PzLPAvRFx90SHnJCWZ0FEBPDxiQ43YW3OIiLmgWvNg/6Xk55xUkZ4jHwnM38AvKvwY+RjwKOb3N/qMbTRdl668aMTetqcxSXgzmadwGsTmGsntDkLgAeBH01kop3T5iw+CfwcoPLfbGh3FruADzXrt1L0MZKZzwC/3WRL28fQP2znpZtOPjqhiKFnkZk/BoiIO5s/vzqx6SZr6Fk0l/T2AteBks/aGm0eI/cCH23eu/L2zPz6hGabtDZn8QTwbET8Cni68GNkmDZn9f9M6pexY390QkHD/jkfBb45mVF23K3O4hjrb8J7M7nVWbwNeC4zvwVkc526uludxTzwOPALep+b9WbXqpvbGXo/OqGn1T9n88vHn2Tm2qQG2wFtzmIv8EHgA8Chwpf02pzFy8CLzfpFWjx7e4NqcxYfyczlzPw28OuIuG9i091eRu7mdobej07oGXoWTczuyMxLEfGeiDg46SEnZOhZZOZTmXkOeAG4lJkVL+dBu8fIT4G/f6DXPuDKhGabtDZn8fsN65eA8pduImJXRLyz7+b+s3pu6PfZznfGRsQ3WH+54HXW/6W8PzO/tuH+XcC/sn6d6YXiL68cdhaPA//U/PE+4Ehm/nnig07AsLNo9kwDj7H+DPaLmbn6um9UQIv/LqaArwDPA2/Z7CV3b3QtzuK9wD8DfwLekZn/uSODbrOIeAj4D+BzwB+Az2fmZ/r2/OOsMvO/h35PPwJBkmrznbGSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScX8DfvAs3vjWN7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot() # 只返回一个画布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 432x288 with 1 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x19cb8575358>)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD8CAYAAAB5Pm/hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADHxJREFUeJzt3E+InXe5wPHv08SUsbHImFETylC9AbMoKOkYcO4mXVgnoFR00YVWCuLAxYUhSBX/EYK9XLh1kQtu5oL0cnO1koWVbqZujEIW1gyt4aJZxMClNUGnmahUU+vicTGvnrmnJ3Pec+adM+nT72f1yzm/mXn6a8+3J++ccyIzkSTVdcdODyBJ2l6GXpKKM/SSVJyhl6TiDL0kFWfoJam4VqGPiIeH3H8yIr4QEZ/uZixJUleGhj4iPgY8usn9h4GbmXkaOBoRe7obT5K0VUNDn5nPAL/dZMsx4Hyzvgwc6WAuSVJHdnfwPQ4Aq816Ddg/aFNELAKLAHfdddf9hw4d6uBHS9Kbx8rKysuZOTPq13UR+o0CGPiZCpm5BCwBzM3N5YULFzr+0ZJUW0T83zhf18Wrbq4C+5r1NHCtg+8pSerISKGPiF0R8c6+m5eB+WZ9EHiui8EkSd1o86qbh4AHIuJBYA54YuP9mbkCTEXEceBcZv51WyaVJI1l6DX6zPwh8MMNN/1swJ5TXQ4lSeqO74yVpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpuN1tNkXESeAGcD0zzwy4fxb4MLAGTGXmd7scUpI0vqHP6CPiMHAzM08DRyNiz4BtjwDfycwfAO+KiLs7nlOSNKY2l26OAeeb9WXgyIA9u4APNeu3Aq9tfTRJUhfaXLo5AKw26zVg/4A9TwDPRsSvgKcz89X+DRGxCCwCzM7OjjetJGlko/4yNoAccPs88DjwC5qY98vMpcycy8y5mZmZEX+sJGlcbUJ/FdjXrKeBawP2fCQzlzPz28CvI+K+rgaUJG1Nm9Avs/6MHeAgcDEipvv2/H7D+iXgdZduJEk7Y2joM3MFmIqI48A5YAE40bftexHxSER8AnglMy93PqkkaSytXkefmaf6bjrbd/8V4EpXQ0mSuuM7YyWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9Jxe1usykiTgI3gOuZeeYWez4LvALcn5mPdTahJGlLhj6jj4jDwM3MPA0cjYg9A/bMA9cy8/vAL7sfU5I0rjaXbo4B55v1ZeDIgD2fBH4OkJlPdjKZJKkTbS7dHABWm/UasH/AnnuBj0bENPD2zPx6/4aIWAQWAWZnZ8caVpI0ulF/GRtADrj9bcBzmfktICPidSXPzKXMnMvMuZmZmTFGlSSNo03orwL7mvU0cG3AnpeBF5v1iwx+1i9J2gFtQr8MzDfrg8DF5hLNRj8F5pr1PuBKN+NJkrZqaOgzcwWYiojjwDlgATjRt+2/gAci4hPAlcxcRZJ0W2j1OvrMPNV309m++28Cr/sFrCRp5/nOWEkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekorb3WZTRJwEbgDXM/PMJvsWgHdn5pOdTCdJ2rKhz+gj4jBwMzNPA0cjYs8t9gXw8Y7nkyRtUZtLN8eA8836MnDkFvseBH7UxVCSpO60Cf0BYLVZrwH7+zdExC5gb3P/QBGxGBEXIuLC6urqrbZJkjo26i9jA8gBtx8Dljf7wsxcysy5zJybmZkZ8cdKksbVJvRXgX3Nehq4NmDPXuCDwAeAQxFxTzfjSZK2qk3ol4H5Zn0QuBgR0xs3ZOZTmXkOeAG4lJkvdTqlJGlsQ0OfmSvAVEQcB84BC8CJ/n1N/BeAByLCazOSdJto9Tr6zDzVd9PZAXvWgC93MZQkqTu+M1aSijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVNzuNpsi4iRwA7iemWcG3L8XeBj4I3AgM093OaQkaXxDn9FHxGHgZhPvoxGxZ8C2R4DnM/MscG9E3N3xnJKkMbW5dHMMON+sLwNHBuy5BNzZrBN4beujSZK60ObSzQFgtVmvAfv7N2TmjwEi4s7mz6/274mIRWARYHZ2dsxxJUmjGvWXscH6M/ZbeRT45qA7MnMpM+cyc25mZmbEHytJGleb0F8F9jXraeDaoE0RsQD8JDPXOppNktSBNqFfBuab9UHgYkRMb9wQEfcAd2TmpYh4T0Qc7HhOSdKYhoY+M1eAqYg4DpwDFoATfdv+BfhMRDwFPMP63wIkSbeBVq+jz8xTfTed7bv/q51NJEnqlO+MlaTiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqbjdbTZFxEngBnA9M88MuH8X8G/A74CLmflsl0NKksY39Bl9RBwGbmbmaeBoROwZsO0h4EJm/jvwqY5nlCRtQZtLN8eA8836MnBkyJ4/R8Q9HcwmSepAm0s3B4DVZr0G7G+556WNGyJiEVhs/viXiPjfkaetaR/w8k4PcZvwLHo8ix7Poud943xRq2v0GwSQ4+zJzCVgCSAiLmTm3Ig/uyTPosez6PEsejyLnoi4MM7Xtbl0c5X1/6MCTAPXxtwjSdoBbUK/DMw364PAxYiY3mTPVGb+pqP5JElbNDT0mbkCTEXEceAcsACc6Nv2NDAXEV8C/qfFz10acc7KPIsez6LHs+jxLHrGOovIHHbJXZL0RuY7YyWpOEMvScWN+vLKkfjRCT0tzmIv8DDwR+BA807kkoadxYZ9C8C7M/PJCY02cW3OIiI+C7wC3J+Zj01wvIlq8RiZBT7M+nt1pjLzu5OdcHIi4uHM/P4m95+kxWPo77btGb0fndDT8iweAZ7PzLPAvRFx90SHnJCWZ0FEBPDxiQ43YW3OIiLmgWvNg/6Xk55xUkZ4jHwnM38AvKvwY+RjwKOb3N/qMbTRdl668aMTetqcxSXgzmadwGsTmGsntDkLgAeBH01kop3T5iw+CfwcoPLfbGh3FruADzXrt1L0MZKZzwC/3WRL28fQP2znpZtOPjqhiKFnkZk/BoiIO5s/vzqx6SZr6Fk0l/T2AteBks/aGm0eI/cCH23eu/L2zPz6hGabtDZn8QTwbET8Cni68GNkmDZn9f9M6pexY390QkHD/jkfBb45mVF23K3O4hjrb8J7M7nVWbwNeC4zvwVkc526uludxTzwOPALep+b9WbXqpvbGXo/OqGn1T9n88vHn2Tm2qQG2wFtzmIv8EHgA8Chwpf02pzFy8CLzfpFWjx7e4NqcxYfyczlzPw28OuIuG9i091eRu7mdobej07oGXoWTczuyMxLEfGeiDg46SEnZOhZZOZTmXkOeAG4lJkVL+dBu8fIT4G/f6DXPuDKhGabtDZn8fsN65eA8pduImJXRLyz7+b+s3pu6PfZznfGRsQ3WH+54HXW/6W8PzO/tuH+XcC/sn6d6YXiL68cdhaPA//U/PE+4Ehm/nnig07AsLNo9kwDj7H+DPaLmbn6um9UQIv/LqaArwDPA2/Z7CV3b3QtzuK9wD8DfwLekZn/uSODbrOIeAj4D+BzwB+Az2fmZ/r2/OOsMvO/h35PPwJBkmrznbGSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScX8DfvAs3vjWN7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots() # 返回一个元素，包含两个元素：画布与子图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots() # 返回一个元素，包含两个元素：画布与子图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD8CAYAAAB5Pm/hAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAADHxJREFUeJzt3E+InXe5wPHv08SUsbHImFETylC9AbMoKOkYcO4mXVgnoFR00YVWCuLAxYUhSBX/EYK9XLh1kQtu5oL0cnO1koWVbqZujEIW1gyt4aJZxMClNUGnmahUU+vicTGvnrmnJ3Pec+adM+nT72f1yzm/mXn6a8+3J++ccyIzkSTVdcdODyBJ2l6GXpKKM/SSVJyhl6TiDL0kFWfoJam4VqGPiIeH3H8yIr4QEZ/uZixJUleGhj4iPgY8usn9h4GbmXkaOBoRe7obT5K0VUNDn5nPAL/dZMsx4Hyzvgwc6WAuSVJHdnfwPQ4Aq816Ddg/aFNELAKLAHfdddf9hw4d6uBHS9Kbx8rKysuZOTPq13UR+o0CGPiZCpm5BCwBzM3N5YULFzr+0ZJUW0T83zhf18Wrbq4C+5r1NHCtg+8pSerISKGPiF0R8c6+m5eB+WZ9EHiui8EkSd1o86qbh4AHIuJBYA54YuP9mbkCTEXEceBcZv51WyaVJI1l6DX6zPwh8MMNN/1swJ5TXQ4lSeqO74yVpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpuN1tNkXESeAGcD0zzwy4fxb4MLAGTGXmd7scUpI0vqHP6CPiMHAzM08DRyNiz4BtjwDfycwfAO+KiLs7nlOSNKY2l26OAeeb9WXgyIA9u4APNeu3Aq9tfTRJUhfaXLo5AKw26zVg/4A9TwDPRsSvgKcz89X+DRGxCCwCzM7OjjetJGlko/4yNoAccPs88DjwC5qY98vMpcycy8y5mZmZEX+sJGlcbUJ/FdjXrKeBawP2fCQzlzPz28CvI+K+rgaUJG1Nm9Avs/6MHeAgcDEipvv2/H7D+iXgdZduJEk7Y2joM3MFmIqI48A5YAE40bftexHxSER8AnglMy93PqkkaSytXkefmaf6bjrbd/8V4EpXQ0mSuuM7YyWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9Jxe1usykiTgI3gOuZeeYWez4LvALcn5mPdTahJGlLhj6jj4jDwM3MPA0cjYg9A/bMA9cy8/vAL7sfU5I0rjaXbo4B55v1ZeDIgD2fBH4OkJlPdjKZJKkTbS7dHABWm/UasH/AnnuBj0bENPD2zPx6/4aIWAQWAWZnZ8caVpI0ulF/GRtADrj9bcBzmfktICPidSXPzKXMnMvMuZmZmTFGlSSNo03orwL7mvU0cG3AnpeBF5v1iwx+1i9J2gFtQr8MzDfrg8DF5hLNRj8F5pr1PuBKN+NJkrZqaOgzcwWYiojjwDlgATjRt+2/gAci4hPAlcxcRZJ0W2j1OvrMPNV309m++28Cr/sFrCRp5/nOWEkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekorb3WZTRJwEbgDXM/PMJvsWgHdn5pOdTCdJ2rKhz+gj4jBwMzNPA0cjYs8t9gXw8Y7nkyRtUZtLN8eA8836MnDkFvseBH7UxVCSpO60Cf0BYLVZrwH7+zdExC5gb3P/QBGxGBEXIuLC6urqrbZJkjo26i9jA8gBtx8Dljf7wsxcysy5zJybmZkZ8cdKksbVJvRXgX3Nehq4NmDPXuCDwAeAQxFxTzfjSZK2qk3ol4H5Zn0QuBgR0xs3ZOZTmXkOeAG4lJkvdTqlJGlsQ0OfmSvAVEQcB84BC8CJ/n1N/BeAByLCazOSdJto9Tr6zDzVd9PZAXvWgC93MZQkqTu+M1aSijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVNzuNpsi4iRwA7iemWcG3L8XeBj4I3AgM093OaQkaXxDn9FHxGHgZhPvoxGxZ8C2R4DnM/MscG9E3N3xnJKkMbW5dHMMON+sLwNHBuy5BNzZrBN4beujSZK60ObSzQFgtVmvAfv7N2TmjwEi4s7mz6/274mIRWARYHZ2dsxxJUmjGvWXscH6M/ZbeRT45qA7MnMpM+cyc25mZmbEHytJGleb0F8F9jXraeDaoE0RsQD8JDPXOppNktSBNqFfBuab9UHgYkRMb9wQEfcAd2TmpYh4T0Qc7HhOSdKYhoY+M1eAqYg4DpwDFoATfdv+BfhMRDwFPMP63wIkSbeBVq+jz8xTfTed7bv/q51NJEnqlO+MlaTiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqThDL0nFGXpJKs7QS1Jxhl6SijP0klScoZek4gy9JBVn6CWpOEMvScUZekkqztBLUnGGXpKKM/SSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScYZekooz9JJUnKGXpOIMvSQVZ+glqbjdbTZFxEngBnA9M88MuH8X8G/A74CLmflsl0NKksY39Bl9RBwGbmbmaeBoROwZsO0h4EJm/jvwqY5nlCRtQZtLN8eA8836MnBkyJ4/R8Q9HcwmSepAm0s3B4DVZr0G7G+556WNGyJiEVhs/viXiPjfkaetaR/w8k4PcZvwLHo8ix7Poud943xRq2v0GwSQ4+zJzCVgCSAiLmTm3Ig/uyTPosez6PEsejyLnoi4MM7Xtbl0c5X1/6MCTAPXxtwjSdoBbUK/DMw364PAxYiY3mTPVGb+pqP5JElbNDT0mbkCTEXEceAcsACc6Nv2NDAXEV8C/qfFz10acc7KPIsez6LHs+jxLHrGOovIHHbJXZL0RuY7YyWpOEMvScWN+vLKkfjRCT0tzmIv8DDwR+BA807kkoadxYZ9C8C7M/PJCY02cW3OIiI+C7wC3J+Zj01wvIlq8RiZBT7M+nt1pjLzu5OdcHIi4uHM/P4m95+kxWPo77btGb0fndDT8iweAZ7PzLPAvRFx90SHnJCWZ0FEBPDxiQ43YW3OIiLmgWvNg/6Xk55xUkZ4jHwnM38AvKvwY+RjwKOb3N/qMbTRdl668aMTetqcxSXgzmadwGsTmGsntDkLgAeBH01kop3T5iw+CfwcoPLfbGh3FruADzXrt1L0MZKZzwC/3WRL28fQP2znpZtOPjqhiKFnkZk/BoiIO5s/vzqx6SZr6Fk0l/T2AteBks/aGm0eI/cCH23eu/L2zPz6hGabtDZn8QTwbET8Cni68GNkmDZn9f9M6pexY390QkHD/jkfBb45mVF23K3O4hjrb8J7M7nVWbwNeC4zvwVkc526uludxTzwOPALep+b9WbXqpvbGXo/OqGn1T9n88vHn2Tm2qQG2wFtzmIv8EHgA8Chwpf02pzFy8CLzfpFWjx7e4NqcxYfyczlzPw28OuIuG9i091eRu7mdobej07oGXoWTczuyMxLEfGeiDg46SEnZOhZZOZTmXkOeAG4lJkVL+dBu8fIT4G/f6DXPuDKhGabtDZn8fsN65eA8pduImJXRLyz7+b+s3pu6PfZznfGRsQ3WH+54HXW/6W8PzO/tuH+XcC/sn6d6YXiL68cdhaPA//U/PE+4Ehm/nnig07AsLNo9kwDj7H+DPaLmbn6um9UQIv/LqaArwDPA2/Z7CV3b3QtzuK9wD8DfwLekZn/uSODbrOIeAj4D+BzwB+Az2fmZ/r2/OOsMvO/h35PPwJBkmrznbGSVJyhl6TiDL0kFWfoJak4Qy9JxRl6SSrO0EtScX8DfvAs3vjWN7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cb6de9470>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 当subplots指定多个字图的时候：\n",
    "fig, ax = plt.subplots(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB85757B8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB8529CC0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB6DF3240>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB87F9A90>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB6FCDD30>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB6C54898>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB85757B8>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB8529CC0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x0000019CB6DF3240>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 可以通过索引访问各个子图\n",
    "ax[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cb85757b8>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cb87f9a90>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2,3)\n",
    "plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)  # 解决坐标轴、标题遮挡问题\n",
    "# 可以针对每一个子图进行画图：\n",
    "ax[0][1].plot([1,2,3])\n",
    "ax[1,2].set_title('title',fontsize=12, color='r')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
